Cascaded networks have been widely applied in the segmentation of normal tissues and lesions and the segmentation of different types of lesions, including the segmentation of liver lesions, brain tumors, sclerosis lesions and prostate cancers [1]} [2]} [3]} [4]}. For example, Awad et al.[5]} presented a cascaded framework called CU-Net to perform automatic segmentation of liver and lesions in CT scans. They also provided useful information and interpretation which could guide clinical treatments. Xi et al. [6]} proposed a Cascaded U-ResNets which follows a novel vertical cascade strategy, and different types of loss functions were evaluated in their work. Apart from liver lesion segmentation, the cascade strategy is popular in BraTS challenges as well. For instance, the Top-2 solutions [7]} [8]} of BraTS 2019 challenge are both cascaded networks with different cascade strategies.
